SOTAVerified

Super-Resolution

Super-Resolution is a task in computer vision that involves increasing the resolution of an image or video by generating missing high-frequency details from low-resolution input. The goal is to produce an output image with a higher resolution than the input image, while preserving the original content and structure.

( Credit: MemNet )

Papers

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Showing 101–110 of 3874 papers

TitleStatusHype
A Tour of Convolutional Networks Guided by Linear InterpretersCode2
Denoising Diffusion Models for Plug-and-Play Image RestorationCode2
Deep Constrained Least Squares for Blind Image Super-ResolutionCode2
FLowHigh: Towards Efficient and High-Quality Audio Super-Resolution with Single-Step Flow MatchingCode2
Deep learning-driven pulmonary artery and vein segmentation reveals demography-associated vasculature anatomical differencesCode2
Frequency-Assisted Mamba for Remote Sensing Image Super-ResolutionCode2
Denoising Diffusion Restoration ModelsCode2
GenN2N: Generative NeRF2NeRF TranslationCode2
Distillation-Supervised Convolutional Low-Rank Adaptation for Efficient Image Super-ResolutionCode2
Efficient Long-Range Attention Network for Image Super-resolutionCode2
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified